Add model card for Parcae-xlarge-1.3B

README.md

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+---
+pipeline_tag: text-generation
+---
+
+# Parcae-xlarge-1.3B
+
+Parcae is a novel stable, looped architecture for language modeling. Unlike traditional fixed-depth architectures that scale by increasing parameter counts, Parcae increases FLOPs by sending activations through a block of layers in a loop. It addresses instability issues in prior looped models by recasting looping as a nonlinear time-variant dynamical system and constraining the spectral norm of injection parameters.
+
+- **Paper:** [Parcae: Scaling Laws For Stable Looped Language Models](https://huggingface.co/papers/2604.12946)
+- **Project Page:** [https://sandyresearch.github.io/parcae/](https://sandyresearch.github.io/parcae/)
+- **Repository:** [https://github.com/sandyresearch/parcae](https://github.com/sandyresearch/parcae)
+
+## Installation
+
+To use this model, you can install the `parcae-lm` package:
+
+```bash
+pip install parcae-lm
+```
+
+## Usage
+
+You can load the pretrained weights using the `parcae_lm` library:
+
+```python
+import parcae_lm
+
+# Load this pretrained model from HuggingFace
+model = parcae_lm.from_pretrained("SandyResearch/parcae-xlarge-1_3b")
+```
+
+## Model Details
+
+This specific checkpoint is the 1.3B parameter variant of Parcae, trained on the FineWeb-Edu dataset.
+
+| Model | Parameters | Prelude | Core | Coda | Model dim. | Recurrence |
+|-------|-----------|---------|------|------|-----------|------------|
+| Parcae-1.3B | 1.3B | 8 | 8 | 8 | 1536 | 8 |
+
+**Note:** These are base models without any form of downstream modification (instruction tuning, etc.).
+
+## Citation
+
+```bibtex
+@misc{prairie2026parcaescalinglawsstable,
+      title={Parcae: Scaling Laws For Stable Looped Language Models}, 
+      author={Hayden Prairie and Zachary Novack and Taylor Berg-Kirkpatrick and Daniel Y. Fu},
+      year={2026},
+      eprint={2604.12946},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2604.12946}, 
+}
+```
+
+## References
+
+This code-base was built on `karpathy/nanochat`, `seal-rg/recurrent-pretraining`, and `Lightning-AI/litgpt`.